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Record W2046072654 · doi:10.1016/j.jom.2011.12.002

Too much of a good thing: The impact of product variety on operations and sales performance

2012· article· en· W2046072654 on OpenAlexaff
Xiang Wan, Philip T. Evers, Martin Dresner

Bibliographic record

VenueJournal of Operations Management · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsVariety (cybernetics)BusinessProduct (mathematics)MarketingIndustrial organizationCommerceComputer scienceMathematics

Abstract

fetched live from OpenAlex

Abstract We examine the impact of product variety decisions on an operational measure – unit fill rate – and on sales performance. Results are estimated using weekly data over three years from 108 distribution centers of a major soft drink bottler. Our results show that fill rates are negatively associated with product variety at a diminishing rate. In addition, we examine the total effect of product variety on sales including both the direct effect and the indirect effect through operations performance. The total impact of product variety on sales initially is positive, although at a diminishing rate. However, beyond a certain level, increased product variety actually results in lower sales; that is, “too much of a good thing”. Thus, the findings provide a comprehensive understanding of the impact of product variety on operations and sales performance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.246
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2012
Admission routes1
Has abstractyes

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